Imaging of macular diseases with optical coherence tomography

Prediction of Postoperative Macular Hole Status by Automated Preoperative Retinal OCT Analysis: A Narrative Review

Optical coherence tomography (OCT) is a non-invasive imaging modality essential for macular hole (MH) management. Artificial intelligence (AI) algorithms could be applied to OCT to garner insights for MH prognosis and outcomes. The objective was to review literature assessing automated image analysis algorithms in predicting postoperative outcomes for MH patients based on OCT images. A narrative search of all available published studies in peer-reviewed journals was conducted up to June 2023 following PRISMA guidelines. Three hundred sixty-eight publications underwent screening, with 14 selected for full-text review and seven determined as relevant. In MH status prediction, AI models achieved an area under the curve (AUC) of 83.6% to 98.4%. For postoperative visual acuity prediction, algorithm performance ranged from AUCs of 57% to 85%. In conclusion, novel AI algorithms were found to be predictive for postoperative MH status and postoperative visual acuity. More research in larger populations should be conducted to gauge the value of these novel algorithms in a real-world setting. [Ophthalmic Surg Lasers Imaging Retina 2025;56:372-377.].

Application of generative adversarial networks in the restoration of blurred optical coherence tomography images caused by optical media opacity in eyes

PURPOSE

To assess the application of generative adversarial networks (GANs) to restore the blurred optical coherence tomography (OCT) images caused by optical media opacity in eyes.

METHODS

In this cross-sectional study, a spectral-domain OCT (Zeiss Cirrus 5000, Germany) was used to scan the macula of 510 eyes from 272 Chinese subjects. Optical media opacity was simulated with an algorithm for training set (420 normal eyes). Images for three test sets were from the following: 56 normal eyes before and after fitting neutral density filter (NDF), 34 eyes before and after cataract surgeries and 90 eyes processed by algorithm. GANs of pix2pix was trained with training set and restored blurred images in test sets. Structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR) were used to evaluate the performance of GANs.

RESULTS

PSNR for test sets before and after image restoration was 18.37±0.44 and 19.94±0.29 for NDF (p＜0.01), 16.65±0.99 and 16.91±0.26 for cataract (p=0.68) and 18.33±0.55 and 20.83±0.41 for algorithm regenerated graph (p＜0.01), respectively. SSIM for test sets before and after image restoration was 0.85±0.02 and 1.00±0.00 for NDF (p＜0.01), 0.92±0.07 and 0.97±0.02 for cataract (p＜0.01) and 0.86±0.02 and 0.99±0.01 for algorithm regenerated graph (p＜0.01), respectively.

CONCLUSIONS

GANs can be used to restore blurred OCT images caused by optical media opacity in eyes. Future studies are warranted to optimise this technique before the application in clinical practice.

Pioneering evaluation in Brazil of microscope-integrated optical coherence tomography with a three-dimensional digital visualization system during pars plana vitrectomy for the treatment of macular hole

BACKGROUND

This study aimed to characterize the clinical results and usability of intraoperative optical coherence tomography (iOCT) associated with a digital visualization system in vitreoretinal surgery for macular hole correction.

METHODS

This is a descriptive observational study of patients undergoing vitreoretinal surgery for macular hole at Brazilian Eye Surgery Center in which the digital visualization system associated with iOCT was used. Anatomical and functional results were collected 6 months after surgery. Macular hole closure rates, pre- and post-operative visual acuity were measured in addition to surgeon feedback and the percentage in which the technology allowed intraoperative decision-making.

RESULTS

25 eyes of 25 patients were included in the study. The mean preoperative visual acuity was 20/100, ranging from 20/50 to less than 20/400, and postoperative visual acuity was 20/60, ranging from 20/25 to less than 20/400. The time spent with iOCT did not result in surgical delay, as the average time spent was 3.24 extra minutes spent per surgery. Closure of the macular hole was achieved successfully in 92% of cases. In 8% of them surgical success in closing the macular hole was achieved after a new fluid-gas exchange in the office. The surgeon preferred real-time iOCT and, in 4% (1/25) of cases, it influenced the change in surgical technique, preventing unnecessary ILM (Internal Limiting Membrane) peeling after complete removal of the posterior hyaloid and closing the macular hole. In all cases the surgeon reported valid feedback regarding the use of information provided by real-time OCT. This tool was valid for confirming complete ILM peeling in all cases in which it was performed. Finally, iOCT made it possible to identify the appropriate location to begin creating the ILM flap in 2 cases (8%) both of fragile retina; It prevented a new injection of dyes to identify residual ILM in 8% of cases (2/25) and allowed verification of the correct positioning of the pedicled ILM flap over the hole in 16% (4/25) of cases. Therefore, in 36% of cases (9/25) iOCT was essential for the final surgical outcome.

CONCLUSION

This study suggests that the use of iOCT integrated with a digital viewing microscope for the treatment of macular holes offers high standard usability and effectiveness for visualizing structures, and impact favorably on decision-making process during pars-plana vitrectomy. These findings suggest that in the near future, expanded use of iOCT could significantly improve tissue management at the vitreomacular interface and improve anatomical and functional results.

Oculomics: Current concepts and evidence

The eye provides novel insights into general health, as well as pathogenesis and development of systemic diseases. In the past decade, growing evidence has demonstrated that the eye's structure and function mirror multiple systemic health conditions, especially in cardiovascular diseases, neurodegenerative disorders, and kidney impairments. This has given rise to the field of oculomics-the application of ophthalmic biomarkers to understand mechanisms, detect and predict disease. The development of this field has been accelerated by three major advances: 1) the availability and widespread clinical adoption of high-resolution and non-invasive ophthalmic imaging ("hardware"); 2) the availability of large studies to interrogate associations ("big data"); 3) the development of novel analytical methods, including artificial intelligence (AI) ("software"). Oculomics offers an opportunity to enhance our understanding of the interplay between the eye and the body, while supporting development of innovative diagnostic, prognostic, and therapeutic tools. These advances have been further accelerated by developments in AI, coupled with large-scale linkage datasets linking ocular imaging data with systemic health data. Oculomics also enables the detection, screening, diagnosis, and monitoring of many systemic health conditions. Furthermore, oculomics with AI allows prediction of the risk of systemic diseases, enabling risk stratification, opening up new avenues for prevention or individualized risk prediction and prevention, facilitating personalized medicine. In this review, we summarise current concepts and evidence in the field of oculomics, highlighting the progress that has been made, remaining challenges, and the opportunities for future research.

Coherence synthesis in nonlinear optics

It is commonly assumed that nonlinear frequency conversion requires lasers with high coherence; however, this assumption has constrained our broader understanding of coherence and overlooked the potential role of incoherence in nonlinear interactions. In this work, we study the synthesis of optical spatial coherence in second harmonic generation using quadratic nonlinear photonic crystals. We demonstrate a method where the second harmonic coherence is customized by employing quantitative phase retrieval and a complex square-root filter sequentially on fundamental frequency speckles. As a proof-of-concept, we experimentally show incoherent imaging of a smiley face transitioning from infrared to visible light. Moreover, we apply this method to produce two representative types of structured light beams in second harmonic generation: incoherent vortex and Airy beams. During the nonlinear synthesis of incoherent vortex beams, we have, for the first time, experimentally verified the conservation of orbital angular momentum in the nonlinear frequency conversion process of a low-coherence source. Furthermore, the generated second-harmonic incoherent Airy beam preserves the self-acceleration characteristics of its fundamental frequency counterpart, remaining unaffected by reductions in coherence. Our results not only deepen the fundamental understanding of optical coherence but also unlock exciting possibilities for applications in infrared imaging and fluorescence microscopy where optical nonlinear interactions play an important role.

OCT5k: A dataset of multi-disease and multi-graded annotations for retinal layers

Publicly available open-access OCT datasets for retinal layer segmentation have been limited in scope, often being small in size, specific to a single disease, or containing only one grading. This dataset improves upon this with multi-grader and multi-disease labels for training machine learning-based algorithms. The proposed dataset covers three subsets of scans (Age-related Macular Degeneration, Diabetic Macular Edema, and healthy) and annotations for two types of tasks (semantic segmentation and object detection). This dataset compiled 5016 pixel-wise manual labels for 1672 OCT scans featuring 5 layer boundaries for three different disease classes to support development of automatic techniques. A subset of data (566 scans across 9 classes of disease biomarkers) was subsequently labeled for disease features for 4698 bounding box annotations. To minimize bias, images were shuffled and distributed among graders. Retinal layers were corrected, and outliers identified using the interquartile range (IQR). This step was iterated three times, improving layer annotations' quality iteratively, ensuring a reliable dataset for automated retinal image analysis.

Optical coherence tomography findings in patients with diabetic macular edema: A retrospective analysis

BACKGROUND

Diabetic macular edema (DME) is a leading cause of vision loss in diabetic people. DME can be treated with various medications, including intravitreal injections, laser therapy, and surgery. Early detection and treatment of DME is essential to prevent vision loss. The study aimed to describe patients' demographic and clinical characteristics with DME, optical coherence tomography (OCT) findings, and visual acuity outcomes.

METHODOLOGY

A retrospective study reviewed case records of patients with DME between 2017 and 2020. Demographic data, clinical characteristics, and examination results were extracted and analyzed using Microsoft Excel (2013). All patients clinically diagnosed with DME underwent assessment by OCT examination. DME was classified based on OCT findings. Statistical significance was observed at P < 0.05.

RESULTS

This retrospective study included 213 eyes of 134 patients, of which 77.6% were male and 22.4% were female. Nonproliferative diabetic retinopathy (NPDR) was present in 51.64% of eyes, and PDR was present in 48.36%. Focal, diffuse, and cystoid macular edema was observed in 68, 31, and 65 eyes, respectively. Tractional macular edema was seen in 16 eyes with posterior hyaloid traction, 13 with epiretinal membrane (ERM), and one with both conditions. DME associated with subretinal fluid (SRF) detachment was seen in 8.92% of eyes. The mean (standard deviation) central retinal thickness was 284.5 (28.9), 434.0 (97.5), 426.5 (27.5), 510.5 (14.1), and 465.5 (280.7) μm in focal, diffuse, cystoid, ERM, and SRF, respectively. Increased central retinal thickness was associated with decreased visual acuity (P < 0.05).

CONCLUSION

The findings of this study suggest that DME is a common and visually significant complication of diabetes. The OCT findings can be used to classify DME into different subtypes, which may help to guide treatment decisions. Focal edema was the most common type of DME with the least central retinal thickness. In NPDR, focal macular edema was the most common; in PDR, cystoid edema was the most common. Cystoid edema was the most common type in the subgroup of patients with recurrent DME following anti-vascular endothelial growth factor injection.

Optical Coherence Tomography Features in Fovea-Off Exudative vs Rhegmatogenous Retinal Detachment

PURPOSE

To describe the optical coherence tomography (OCT) features that can differentiate eyes with fovea-off exudative retinal detachment (ERD) vs rhegmatogenous retinal detachment (RRD), with particular attention to outer retinal corrugations (ORCs).

DESIGN

Multicenter, retrospective cross-sectional study.

METHODS

Multicenter, retrospective cross-sectional study of patients diagnosed with unilateral or bilateral fovea-off ERD or primary, acute, fovea-off RRD between 2016 and 2021. This study was performed with the approval from the Research Ethics Board at the University of Toronto and was conducted in accordance with the Declaration of Helsinki. Patients with any ERD etiology and evidence of extensive, bullous fovea-off detachment and in the RRD group: consecutive patients with acute, primary fovea-off RRD with good quality baseline SD-OCT imaging were included. Patients with exudative choroidal neovascularization from any etiology, optic nerve pit, significant media opacity, or OCT images with poor quality or low signal strength were excluded. Primary outcome was to describe the morphological features of the macula using SD-OCT in patients diagnosed with ERD vs RRD, with specific interest in ORCs.

RESULTS

One hundred sixty-one eyes (51 ERD and 110 RRD) of 154 patients were included. Fifty-one eyes with ERD presented with 1 of 15 etiologies. ERD were associated with a greater risk of having hyperreflective dots in the outer retina (92.2% vs 74.5%, P = .009), hyperreflective material and dots in the subretinal fluid (72.5% vs 34.5%, P < .001), internal limiting membrane and inner retinal undulations (70.6% vs 39.4%, P < .001), and retinal pigment epithelium undulations (44.9% vs 6.4%, P < .001) compared to RRD. RRD was associated with a greater risk of outer retinal corrugations (80% vs 0%, P < .001), intraretinal fluid (90.9% vs 41.2%, P < .001) and ellipsoid zone thickening (90% vs 66.7%, P < .001) compared to ERD.

CONCLUSION

The presence of ORCs are highly specific for RRD and absent in ERD. This is likely related to differences in the pathophysiology of the diseases process, specifically the content of the subretinal fluid. Understanding the differences in OCT morphological features of ERD vs RRD may aid with diagnosis and management.

Reproducibility of Portable OCT and Comparison with Conventional OCT

Optical coherence tomography (OCT) is an indispensable instrument in ophthalmology; however, some facilities lack permanent OCT devices. ACT100, a portable SD-OCT system, allows for medical examinations at hospitals that do not have OCT and house calls. We investigated the usefulness of ACT100 by examining the reproducibility of retinal thickness measurements in 35 healthy participants with normal eyes using ACT100 and Cirrus. Using two OCTs, the OCT imaging of both eyes of each subject was performed. Macular retinal thickness was evaluated using the average value in nine lesions of the Early Treatment Diabetic Retinopathy Study (ETDRS) circle. Both models captured images in all cases. In the right eye, mean retinal thickness was significantly lower than in the ACT100 group in all regions; however, the measured values correlated well. The intraclass correlation coefficients showed the same high reliability as the Cirrus. The coefficients of variation (CVs) of both models showed little variation and high stability; however, the CV of ACT100 was significantly higher. The left eye was almost identical. Macular retinal thickness measured using ACT100 showed slightly greater variability than that by Cirrus; the reproducibility was good and correlated well with that of Cirrus. This technique is a suitable alternative to conventional OCT.

Global research trends and future directions in diabetic macular edema research: A bibliometric and visualized analysis

BACKGROUND

Diabetic Macular Edema (DME) significantly impairs vision in diabetics, with varied patient responses to current treatments like anti-vascular endothelial growth factor (VEGF) therapy underscoring the necessity for continued research into more effective strategies. This study aims to evaluate global research trends and identify emerging frontiers in DME to guide future research and clinical management.

METHODS

A qualitative and quantitative analysis of publications related to diabetic macular edema retrieved from the Web of Science Core Collection (WoSCC) between its inception and September 4, 2023, was conducted. Microsoft Excel, CiteSpace, VOSviewer, Bibliometrix Package, and Tableau were used for the bibliometric analysis and visualization. This encompasses an examination of the overall distribution of annual output, major countries, regions, institutions, authors, core journals, co-cited references, and keyword analyses.

RESULTS

Overall, 5624 publications were analyzed, indicating an increasing trend in DME research. The United States was identified as the leading country in DME research, with the highest h-index of 135 and 91,841 citations. Francesco Bandello emerged as the most prolific author with 97 publications. Neil M. Bressler has the highest h-index and highest total citation count of 46 and 9692, respectively. The journals "Retina - the Journal of Retinal and Vitreous Diseases" and "Ophthalmology" were highlighted as the most prominent in this field. "Retina" leads with 354 publications, a citation count of 11,872, and an h-index of 59. Meanwhile, "Ophthalmology" stands out with the highest overall citation count of 31,558 and the highest h-index of 90. The primary research focal points in diabetic macular edema included "prevalence and risk factors," "pathological mechanisms," "imaging modalities," "treatment strategies," and "clinical trials." Emerging research areas encompassed "deep learning and artificial intelligence," "novel treatment modalities," and "biomarkers."

CONCLUSION

Our bibliometric analysis delineates the leading role of the United States in DME research. We identified current research hotspots, including epidemiological studies, pathophysiological mechanisms, imaging advancements, and treatment innovations. Emerging trends, such as the integration of artificial intelligence and novel therapeutic approaches, highlight future directions. These insights underscore the importance of collaborative and interdisciplinary approaches in advancing DME research and clinical management.

Generalized 3D registration algorithm for enhancing retinal optical coherence tomography images

Significance

Optical coherence tomography (OCT) has emerged as the standard of care for diagnosing and monitoring the treatment of various ocular disorders due to its noninvasive nature and in vivo volumetric acquisition capability. Despite its widespread applications in ophthalmology, motion artifacts remain a challenge in OCT imaging, adversely impacting image quality. While several multivolume registration algorithms have been developed to address this issue, they are often designed to cater to one specific OCT system or acquisition protocol.

Aim

We aim to generate an OCT volume free of motion artifacts using a system-agnostic registration algorithm that is independent of system specifications or protocol.

Approach

We developed a B-scan registration algorithm that removes motion and corrects for both translational eye movements and rotational angle differences between volumes. Tests were carried out on various datasets obtained from two different types of custom-built OCT systems and one commercially available system to determine the reliability of the proposed algorithm. Additionally, different system specifications were used, with variations in axial resolution, lateral resolution, signal-to-noise ratio, and real-time motion tracking. The accuracy of this method has further been evaluated through mean squared error (MSE) and multiscale structural similarity index measure (MS-SSIM).

Results

The results demonstrate improvements in the overall contrast of the images, facilitating detailed visualization of retinal vasculatures in both superficial and deep vasculature plexus. Finer features of the inner and outer retina, such as photoreceptors and other pathology-specific features, are discernible after multivolume registration and averaging. Quantitative analyses affirm that increasing the number of averaged registered volumes will decrease MSE and increase MS-SSIM as compared to the reference volume.

Conclusions

The multivolume registered data obtained from this algorithm offers significantly improved visualization of the retinal microvascular network as well as retinal morphological features. Furthermore, we have validated that the versatility of our methodology extends beyond specific OCT modalities, thereby enhancing the clinical utility of OCT for the diagnosis and monitoring of ocular pathologies.

Automatic exudate and aneurysm segmentation in OCT images using UNET++ and hyperreflective-foci feature based bagged tree ensemble

Diabetic retinopathy's signs, such as exudates (EXs) and aneurysms (ANs), initially develop from under the retinal surface detectable from optical coherence tomography (OCT) images. Detecting these signs helps ophthalmologists diagnose DR sooner. Detecting and segmenting exudates (EXs) and aneurysms (ANs) in medical images is challenging due to their small size, similarity to other hyperreflective regions, noise presence, and low background contrast. Furthermore, the scarcity of public OCT images featuring these abnormalities has limited the number of studies related to the automatic segmentation of EXs and ANs, and the reported performance of such studies has not been satisfactory. This work proposes an efficient algorithm that can automatically segment these anomalies by improving key steps in the process. The potential area where these hyper-reflective EXs and ANs occur was scoped by our method using a deep-learning U-Net++ program. From this area, the candidates for EX-AN were segmented using the adaptive thresholding method. Nine features based on appearances, locations, and shadow markers were extracted from these candidates. They were trained and tested using bagged tree ensemble classifiers to obtain only EX-AN blobs. The proposed method was tested on a collection of a public dataset comprising 80 images with hand-drawn ground truths. The experimental results showed that our method could segment EX-AN blobs with average recall, precision, and F1-measure as 87.9%, 86.1%, and 87.0%, respectively. Its F1-measure drastically outperformed two comparative methods, binary thresholding and watershed (BT-WS) and adaptive thresholding with shadow tracking (AT-ST), by 78.0% and 82.1%, respectively.

Megahertz multi-parametric ophthalmic OCT system for whole eye imaging

An ultrahigh-speed, wide-field OCT system for the imaging of anterior, posterior, and ocular biometers is crucial for obtaining comprehensive ocular parameters and quantifying ocular pathology size. Here, we demonstrate a multi-parametric ophthalmic OCT system with a speed of up to 1 MHz for wide-field imaging of the retina and 50 kHz for anterior chamber and ocular biometric measurement. A spectrum correction algorithm is proposed to ensure the accurate pairing of adjacent A-lines and elevate the A-scan speed from 500 kHz to 1 MHz for retinal imaging. A registration method employing position feedback signals was introduced, reducing pixel offsets between forward and reverse galvanometer scanning by 2.3 times. Experimental validation on glass sheets and the human eye confirms feasibility and efficacy. Meanwhile, we propose a revised formula to determine the "true" fundus size using all-axial length parameters from different fields of view. The efficient algorithms and compact design enhance system compatibility with clinical requirements, showing promise for widespread commercialization.

Coherent light scattering from cellular dynamics in living tissues

This review examines the biological physics of intracellular transport probed by the coherent optics of dynamic light scattering from optically thick living tissues. Cells and their constituents are in constant motion, composed of a broad range of speeds spanning many orders of magnitude that reflect the wide array of functions and mechanisms that maintain cellular health. From the organelle scale of tens of nanometers and upward in size, the motion inside living tissue is actively driven rather than thermal, propelled by the hydrolysis of bioenergetic molecules and the forces of molecular motors. Active transport can mimic the random walks of thermal Brownian motion, but mean-squared displacements are far from thermal equilibrium and can display anomalous diffusion through Lévy or fractional Brownian walks. Despite the average isotropic three-dimensional environment of cells and tissues, active cellular or intracellular transport of single light-scattering objects is often pseudo-one-dimensional, for instance as organelle displacement persists along cytoskeletal tracks or as membranes displace along the normal to cell surfaces, albeit isotropically oriented in three dimensions. Coherent light scattering is a natural tool to characterize such tissue dynamics because persistent directed transport induces Doppler shifts in the scattered light. The many frequency-shifted partial waves from the complex and dynamic media interfere to produce dynamic speckle that reveals tissue-scale processes through speckle contrast imaging and fluctuation spectroscopy. Low-coherence interferometry, dynamic optical coherence tomography, diffusing-wave spectroscopy, diffuse-correlation spectroscopy, differential dynamic microscopy and digital holography offer coherent detection methods that shed light on intracellular processes. In health-care applications, altered states of cellular health and disease display altered cellular motions that imprint on the statistical fluctuations of the scattered light. For instance, the efficacy of medical therapeutics can be monitored by measuring the changes they induce in the Doppler spectra of livingex vivocancer biopsies.

Multi-Scale-Denoising Residual Convolutional Network for Retinal Disease Classification Using OCT

Macular pathologies can cause significant vision loss. Optical coherence tomography (OCT) images of the retina can assist ophthalmologists in diagnosing macular diseases. Traditional deep learning networks for retinal disease classification cannot extract discriminative features under strong noise conditions in OCT images. To address this issue, we propose a multi-scale-denoising residual convolutional network (MS-DRCN) for classifying retinal diseases. Specifically, the MS-DRCN includes a soft-denoising block (SDB), a multi-scale context block (MCB), and a feature fusion block (FFB). The SDB can determine the threshold for soft thresholding automatically, which removes speckle noise features efficiently. The MCB is designed to capture multi-scale context information and strengthen extracted features. The FFB is dedicated to integrating high-resolution and low-resolution features to precisely identify variable lesion areas. Our approach achieved classification accuracies of 96.4% and 96.5% on the OCT2017 and OCT-C4 public datasets, respectively, outperforming other classification methods. To evaluate the robustness of our method, we introduced Gaussian noise and speckle noise with varying PSNRs into the test set of the OCT2017 dataset. The results of our anti-noise experiments demonstrate that our approach exhibits superior robustness compared with other methods, yielding accuracy improvements ranging from 0.6% to 2.9% when compared with ResNet under various PSNR noise conditions.

Axial super-resolution optical coherence tomography via complex-valued network

Optical coherence tomography (OCT) is a fast and non-invasive optical interferometric imaging technique that can provide high-resolution cross-sectional images of biological tissues. OCT's key strength is its depth resolving capability which remains invariant along the imaging depth and is determined by the axial resolution. The axial resolution is inversely proportional to the bandwidth of the OCT light source. Thus, the use of broadband light sources can effectively improve the axial resolution and however leads to an increased cost. In recent years, real-valued deep learning technique has been introduced to obtain super-resolution optical imaging. In this study, we proposed a complex-valued super-resolution network (CVSR-Net) to achieve an axial super-resolution for OCT by fully utilizing the amplitude and phase of OCT signal. The method was evaluated on three OCT datasets. The results show that the CVSR-Net outperforms its real-valued counterpart with a better depth resolving capability. Furthermore, comparisons were made between our network, six prevailing real-valued networks and their complex-valued counterparts. The results demonstrate that the complex-valued network exhibited a better super-resolution performance than its real-valued counterpart and our proposed CVSR-Net achieved the best performance. In addition, the CVSR-Net was tested on out-of-distribution domain datasets and its super-resolution performance was well maintained as compared to that on source domain datasets, indicating a good generalization capability.

Optical Coherence Tomography-History, Evolution, and Future Prospects: 2023 Lasker-DeBakey Clinical Medical Research Award

In this Viewpoint, 2023 Lasker-DeBakey Clinical Medical Research Award winners James G. Fujimoto, David Huang, and Eric A. Swanson discuss their invention—optical coherence tomography, which allows rapid detection of diseases of the retina that impair vision.

In vivo characterisation of field pea stem wall thickness using optical coherence tomography

BACKGROUND

Modern field pea breeding faces a significant challenge in selecting lines with strong stems that resist lodging. Traditional methods of assessing stem strength involve destructive mechanical tests on mature stems after natural senescence, such as measuring stem flexion, stem buckling or the thickness of dry stems when compressed, but these measurements may not correspond to the strength of stems in the living plant. Optical coherence tomography (OCT) can be used as a noncontact and nondestructive method to measure stem wall thickness in living plants by acquiring two- or three-dimensional images of living plant tissue.

RESULTS

In this proof-of-principle study, we demonstrated in vivo characterisation of stem wall thickness using OCT, with the measurement corrected for the refractive index of the stem tissue. This in vivo characterisation was achieved through real-time imaging of stems, with an acquisition rate of 13 milliseconds per two-dimensional, cross-sectional OCT image. We also acquired OCT images of excised stems and compared the accuracy of in vivo OCT measurements of stem wall thickness with ex vivo results for 10 plants each of two field pea cultivars, Dunwa and Kaspa. In vivo OCT measurements of stem wall thickness have an average percent error of - 3.1% when compared with ex vivo measurements. Additionally, we performed in vivo measurements of both stem wall thickness and stem width at various internode positions on the two cultivars. The results revealed that Dunwa had a uniform stem wall thickness across different internode positions, while Kaspa had a significantly negative slope of [Formula: see text]0.0198 mm/node. Both cultivars exhibited an increase in stem width along the internode positions; however, Dunwa had a rate of increase of 0.1844 mm/node, which is three times higher than that of Kaspa.

CONCLUSIONS

Our study has demonstrated the efficacy of OCT for accurate measurement of the stem wall thickness of live field pea. Moreover, OCT shows that the trends of stem wall thickness and stem width along the internode positions are different for the two cultivars, Dunwa and Kaspa, potentially hinting at differences in their stem strength. This rapid, in vivo imaging method provides a useful tool for characterising physical traits critical in breeding cultivars that are resistant to lodging.

Volumetrically tracking retinal and choroidal structural changes in central serous chorioretinopathy

Central serous chorioretinopathy (CSCR) leads to the accumulation of subretinal fluid and retinal thickness change, which can be readily detected in clinics using optical coherence tomography (OCT). However, current quantification methods usually require sophisticated processing such as retinal layer segmentations, and volumetric visualization of structural changes is generally challenging, which can hinder fast and accurate assessment of disease progression and/or treatment efficacy. In this study, we developed an algorithm that can register the OCT scans acquired from different visits without requiring prior layer segmentation and calculated the three-dimensional (3-D) structural change maps for patients with CSCR. Our results demonstrate that this tool can be useful in monitoring the progression of CSCR and revealing the resolution of pathologies following treatment automatically with minimal pre-processing.

SCORE2 Report 24: Nonlinear Relationship of Retinal Thickness and Visual Acuity in Central Retinal and Hemiretinal Vein Occlusion

PURPOSE

To investigate whether a nonlinear association between central subfield thickness (CST) on spectral-domain OCT and concurrent visual acuity letter score (VALS) exists in eyes treated initially with aflibercept or bevacizumab for macular edema associated with central retinal vein occlusion (CRVO) or hemiretinal vein occlusion (HRVO) in the Study of Comparative Treatments for Retinal Vein Occlusion 2 (SCORE2).

DESIGN

Long-term follow-up after a randomized clinical trial from 64 centers in the United States.

PARTICIPANTS

Participants were followed up to 60 months and treated at investigator discretion after completing the 12-month treatment protocol.

METHODS

Two-segment linear regression models were compared with simple linear regression models of VALS on CST. Pearson correlation coefficients were calculated to assess strength of CST and VALS associations.

MAIN OUTCOME MEASURES

Central subfield thickness was measured by OCT and VALS by the electronic Early Treatment Diabetic Retinopathy Study methodology.

RESULTS

Estimated inflection points, reflecting turning points at which the CST and VALS association changes from positive to negative, calculated at 7 postbaseline visits, range from 217 to 256 μm. A strongly positive correlation exists to the left of each estimated inflection point, ranging from 0.29 (P < 0.01 at month 60) to 0.50 (P < 0.01 at month 12), and a strongly negative correlation exists to the right of each estimated inflection point, ranging from -0.43 (P < 0.01 at month 1) to -0.74 (P < 0.01 at month 24). Randomization statistical tests showed that 2-segment models are favored over 1-segment models for all postbaseline months (P < 0.001 for all tests performed).

CONCLUSIONS

The relationship between CST and VALS in eyes with CRVO or HRVO after treatment with anti-vascular endothelial growth factor (VEGF) therapy is not simply linear. The usually modest correlations between OCT-measured CST and visual acuity belie strong left and right correlations present in 2-segment models. Post-treatment CST close to the estimated inflection points showed the best expected VALS. The SCORE2 participants with a post-treatment CST after treatment close to the estimated inflection points of 217 to 256 μm showed the best VALS. In patients treated with anti-VEGF for macular edema associated with CRVO or HRVO, a thinner retina is not always associated with better VALS.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Volumetrically tracking retinal and choroidal structural changes in central serous chorioretinopathy

Central serous chorioretinopathy (CSCR) leads to accumulation of subretinal fluid and retinal thickness change, which can be readily detected in clinics using optical coherence tomography (OCT). However, current quantification methods usually require sophisticated processing such as retinal layer segmentations, and volumetric visualization of structural changes is generally challenging, which can hinder fast and accurate assessment of disease progression and/or treatment efficacy. In this study, we developed an algorithm that can register the OCT scans acquired from different visits without requiring prior layer segmentation and calculated the three-dimensional (3-D) structural change maps for patients with CSCR. Our results demonstrate that this tool can be useful in monitoring the progression of CSCR and revealing the resolution of pathologies following treatment automatically with minimal pre-processing.

Normative Data for Macular Thickness and Volume for Optical Coherence Tomography in a Diabetic Population without Maculopathies

PURPOSE

The purpose was to establish normative data for the macular thicknesses and volume using spectral-domain optical coherence tomography (SD-OCT) in a diabetic population without maculopathies for use as a reference in diabetic retinopathy (DR) and diabetic macular edema screening programs.

METHODS

This was an observational study nested in a cohort of diabetics from a telemedicine DR screening program. Each patient underwent SD-OCT centered on the fovea. Macular thickness and volume were described and compared using the built-in normative database of the device. Quantile regression models for the 97.5% percentile were fitted to evaluate the predictors of macular thickness and volume.

RESULTS

A total of 3410 eyes (mean age, 62.25 (SD, 0.22) years) were included. Mean (SD) central subfield thickness (CST) was 238.2 (23.7) µm, while center thickness (CT), average thickness (AT), and macular volume (MV) were 205.4 (31.6) µm, 263.9 (14.3) µm, and 7.46 (0.40) mm3, respectively. Para- and perifoveal thicknesses were clinically and statistically significantly thinner in our population than in the normative reference database. The 97.5% percentile of the thickness of all sectors was increased in males and in the para- and perifovea among those with DR.

CONCLUSIONS

All ETDRS sectors were thinner in patients with diabetes than in the reference population, except for the CST, which was the most stable parameter that only changed with sex. The upper cutoff limit to detect diabetic macular edema (DME) was different from that of the reference population and was influenced by conditions related to diabetes, such as DR. Therefore, specific normative data for diabetic patients should be used for the screening and diagnosis of DME using SD-OCT.

Coded aperture snapshot spectral imaging fundus camera

Spectral imaging holds great promise for the non-invasive diagnosis of retinal diseases. However, to acquire a spectral datacube, conventional spectral cameras require extensive scanning, leading to a prolonged acquisition. Therefore, they are inapplicable to retinal imaging because of the rapid eye movement. To address this problem, we built a coded aperture snapshot spectral imaging fundus camera, which captures a large-sized spectral datacube in a single exposure. Moreover, to reconstruct a high-resolution image, we developed a robust deep unfolding algorithm using a state-of-the-art spectral transformer in the denoising network. We demonstrated the performance of the system through various experiments, including imaging standard targets, utilizing an eye phantom, and conducting in vivo imaging of the human retina.

Visualization of surgical maneuvers using intraoperative real-time volumetric optical coherence tomography

Ophthalmic microsurgery is traditionally performed using stereomicroscopes and requires visualization and manipulation of sub-millimeter tissue structures with limited contrast. Optical coherence tomography (OCT) is a non-invasive imaging modality that can provide high-resolution, depth-resolved cross sections, and has become a valuable tool in clinical practice in ophthalmology. While there has been substantial progress in both research and commercialization efforts to bring OCT imaging into live surgery, its use is still somewhat limited due to factors such as low imaging speed, limited scan configurations, and suboptimal data visualization. In this paper we describe, to the best of our knowledge, the translation of the fastest swept-source intraoperative OCT system with real-time volumetric imaging with stereoscopic data visualization provided via a heads-up display into the operating room. Results from a sampling of human anterior segment and retinal surgeries chosen from 93 human surgeries using the system are shown and the benefits that this mode of intrasurgical OCT imaging provides are discussed.

Optical coherence tomography image despeckling based on tensor singular value decomposition and fractional edge detection

Optical coherence tomography (OCT) imaging is a technique that is frequently used to diagnose medical conditions. However, coherent noise, sometimes referred to as speckle noise, can dramatically reduce the quality of OCT images, which has an adverse effect on how OCT images are used. In order to enhance the quality of OCT images, a speckle noise reduction technique is developed, and this method is modelled as a low-rank tensor approximation issue. The grouped 3D tensors are first transformed into the transform domain using tensor singular value decomposition (t-SVD). Then, to cut down on speckle noise, transform coefficients are thresholded. Finally, the inverse transform can be used to produce images with speckle suppression. To further enhance the despeckling results, a feature-guided thresholding approach based on fractional edge detection and an adaptive backward projection technique are also presented. Experimental results indicate that the presented algorithm outperforms several comparison methods in relation to speckle suppression, objective metrics, and edge preservation.

Real-time closed-loop tissue-specific laser osteotomy using deep-learning-assisted optical coherence tomography

This article presents a real-time noninvasive method for detecting bone and bone marrow in laser osteotomy. This is the first optical coherence tomography (OCT) implementation as an online feedback system for laser osteotomy. A deep-learning model has been trained to identify tissue types during laser ablation with a test accuracy of 96.28 %. For the hole ablation experiments, the average maximum depth of perforation and volume loss was 0.216 mm and 0.077 mm³, respectively. The contactless nature of OCT with the reported performance shows that it is becoming more feasible to utilize it as a real-time feedback system for laser osteotomy.

Prediction of postoperative visual acuity in patients with age-related cataracts using macular optical coherence tomography-based deep learning method

Background

To predict postoperative visual acuity (VA) in patients with age-related cataracts using macular optical coherence tomography-based deep learning method.

Methods

A total of 2,051 eyes from 2,051 patients with age-related cataracts were included. Preoperative optical coherence tomography (OCT) images and best-corrected visual acuity (BCVA) were collected. Five novel models (I, II, III, IV, and V) were proposed to predict postoperative BCVA. The dataset was randomly divided into a training (n = 1,231), validation (n = 410), and test set (n = 410). The performance of the models in predicting exact postoperative BCVA was evaluated using mean absolute error (MAE) and root mean square error (RMSE). The performance of the models in predicting whether postoperative BCVA was improved by at least two lines in the visual chart (0.2LogMAR) was evaluated using precision, sensitivity, accuracy, F1 and area under curve (AUC).

Results

Model V containing preoperative OCT images with horizontal and vertical B-scans, macular morphological feature indices, and preoperative BCVA had a better performance in predicting postoperative VA, with the lowest MAE (0.1250 and 0.1194LogMAR) and RMSE (0.2284 and 0.2362LogMAR), and the highest precision (90.7% and 91.7%), sensitivity (93.4% and 93.8%), accuracy (88% and 89%), F1 (92% and 92.7%) and AUCs (0.856 and 0.854) in the validation and test datasets, respectively.

Conclusion

The model had a good performance in predicting postoperative VA, when the input information contained preoperative OCT scans, macular morphological feature indices, and preoperative BCVA. The preoperative BCVA and macular OCT indices were of great significance in predicting postoperative VA in patients with age-related cataracts.

Coded aperture snapshot spectral imaging fundus camera

Spectral imaging holds great promise for the non-invasive diagnosis of retinal diseases. However, to acquire a spectral datacube, conventional spectral cameras require extensive scanning, leading to a prolonged acquisition. Therefore, they are inapplicable to retinal imaging because of the rapid eye movement. To address this problem, we built a coded aperture snapshot spectral imaging fundus camera, which captures a large-sized spectral datacube in a single exposure. Moreover, to reconstruct a high-resolution image, we developed a robust deep unfolding algorithm using a state-of-the-art spectral transformer in the denoising network. We demonstrated the system performance on both standard targets and an eye phantom.

High-Speed Stimulated Raman Scattering Microscopy Using Inertia-Free AOD Scanning

High-throughput stimulated Raman scattering (SRS) microscopy is highly desired for large tissue imaging with chemical specificity. However, the mapping speed remains as the major short board of conventional SRS, primarily owing to the mechanical inertia existing in galvanometers or other laser scanning alternatives. Here, we developed inertia-free acousto-optic deflector (AOD)-based high-speed large-field stimulated Raman scattering microscopy, in which both the speed and integration time are ensured by immune of the mechanical response time. To avoid laser beam distortion induced by the intrinsic spatial dispersion of AODs, two spectral compression systems are implemented to compress the broad-band femtosecond pulse to picosecond laser. We achieved an SRS imaging of a 12 × 8 mm² mouse brain slice in only 8 min at an image resolution of approximately 1 μm and 32 slices from a whole brain in 12 h. The AOD-based inertia-free SRS mapping can be much faster after further upgrading and allow broad-spectrum applications of chemical imaging in the future.

Deep learning-based image enhancement in optical coherence tomography by exploiting interference fringe

Optical coherence tomography (OCT), an interferometric imaging technique, provides non-invasive, high-speed, high-sensitive volumetric biological imaging in vivo. However, systemic features inherent in the basic operating principle of OCT limit its imaging performance such as spatial resolution and signal-to-noise ratio. Here, we propose a deep learning-based OCT image enhancement framework that exploits raw interference fringes to achieve further enhancement from currently obtainable optimized images. The proposed framework for enhancing spatial resolution and reducing speckle noise in OCT images consists of two separate models: an A-scan-based network (NetA) and a B-scan-based network (NetB). NetA utilizes spectrograms obtained via short-time Fourier transform of raw interference fringes to enhance axial resolution of A-scans. NetB was introduced to enhance lateral resolution and reduce speckle noise in B-scan images. The individually trained networks were applied sequentially. We demonstrate the versatility and capability of the proposed framework by visually and quantitatively validating its robust performance. Comparative studies suggest that deep learning utilizing interference fringes can outperform the existing methods. Furthermore, we demonstrate the advantages of the proposed method by comparing our outcomes with multi-B-scan averaged images and contrast-adjusted images. We expect that the proposed framework will be a versatile technology that can improve functionality of OCT.

In vivo corneal elastography: A topical review of challenges and opportunities

Clinical measurement of corneal biomechanics can aid in the early diagnosis, progression tracking, and treatment evaluation of ocular diseases. Over the past two decades, interdisciplinary collaborations between investigators in optical engineering, analytical biomechanical modeling, and clinical research has expanded our knowledge of corneal biomechanics. These advances have led to innovations in testing methods (ex vivo, and recently, in vivo) across multiple spatial and strain scales. However, in vivo measurement of corneal biomechanics remains a long-standing challenge and is currently an active area of research. Here, we review the existing and emerging approaches for in vivo corneal biomechanics evaluation, which include corneal applanation methods, such as ocular response analyzer (ORA) and corneal visualization Scheimpflug technology (Corvis ST), Brillouin microscopy, and elastography methods, and the emerging field of optical coherence elastography (OCE). We describe the fundamental concepts, analytical methods, and current clinical status for each of these methods. Finally, we discuss open questions for the current state of in vivo biomechanics assessment techniques and requirements for wider use that will further broaden our understanding of corneal biomechanics for the detection and management of ocular diseases, and improve the safety and efficacy of future clinical practice.

Speckle attenuation for optical coherence tomography images using the generalized low rank approximations of matrices

A frequently used technology in medical diagnosis is optical coherence tomography (OCT). However, coherent noise, also known as speckle noise, has the potential to severely reduce the quality of OCT images, which would be detrimental to the use of OCT images for disease diagnosis. In this paper, a despeckling method is proposed to effectively reduce the speckle noise in OCT images using the generalized low rank approximations of matrices (GLRAM). Specifically, the Manhattan distance (MD)-based block matching method is first used to find nonlocal similar blocks for the reference one. The left and right projection matrices shared by these image blocks are then found using the GLRAM approach, and an adaptive method based on asymptotic matrix reconstruction is proposed to determine how many eigenvectors are present in the left and right projection matrices. Finally, all the reconstructed image blocks are aggregated to create the despeckled OCT image. In addition, an edge-guided adaptive back-projection strategy is used to improve the despeckling performance of the proposed method. Experiments with synthetic and real OCT images show that the presented method performs well in both objective measurements and visual evaluation.

How should we report the foveal status in eyes with "macula-off" retinal detachment?

Whilst pre- and postoperative multimodal imaging technologies including optical coherence tomography (OCT) have investigated the morphological correlates of worsened visual outcomes in rhegmatogenous retinal detachment (RRD) with foveal involvement, the nomenclature has adhered to the traditional ophthalmoscopy-based and rather vague term "macula-off". This article appraises the current literature with regard to the preoperative assessment and nomenclature of the foveal status in macula involving retinal detachment (MIRD). A literature review of recent publications assessing functional or morphological outcomes in MIRD was conducted, using the search terms "fovea-off" or "macula-off". The search date was April 28^th, 2021. Original studies in English language were included. Case reports, review articles or letters were excluded. Forty relevant articles (range of publication dates: July 29^th, 2020 - April 18^th, 2021) were reviewed to assess the diagnostic modalities used, morphological parameters assessed, and any specific nomenclature introduced to specify the extent of macular detachment. The results suggest widespread variability and inconsistencies with regard to the preoperative assessment, diagnostic modalities and nomenclature used to describe the foveal status in eyes with RRD termed "macula-off". The extent of macular detachment may be classified by a wide range of morphological parameters, including the height of foveal detachment and the ETDRS grid as overlay tool in OCT devices. There is a scientific and clinical need for an updated nomenclature for eyes with "macula-off" RRD. Preoperative OCT findings should be reported on a regular and standardized basis in order to establish a consensus how to report the foveal status in eyes with MIRD.

Deep Learning-Based System for Disease Screening and Pathologic Region Detection From Optical Coherence Tomography Images

Purpose

This study was designed to apply deep learning models in retinal disease screening and lesion detection based on optical coherence tomography (OCT) images.

Methods

We collected 37,138 OCT images from 775 patients and labelled by ophthalmologists. Multiple deep learning models including ResNet50 and YOLOv3 were developed to identify the types and locations of diseases or lesions based on the images.

Results

The model were evaluated using patient-based independent holdout set. For binary classification of OCT images with or without lesions, the performance accuracy was 98.5%, sensitivity was 98.7%, specificity was 98.4%, and the F1 score was 97.7%. For multiclass multilabel disease classification, the models was able to detect vitreomacular traction syndrome and age-related macular degeneration both with an accuracy of more than 99%, sensitivity of more than 98%, specificity of more than 98%, and an F1 score of more than 97%. For lesion location detection, the recalls for different lesion types ranged from 87.0% (epiretinal membrane) to 98.2% (macular pucker).

Conclusions

Deep learning-based models have potentials to aid retinal disease screening, classification and diagnosis with excellent performance, which may serve as useful references for ophthalmologists.

Translational Relevance

The deep learning-based models are capable of identifying and predicting different eye diseases and lesions from OCT images and may have potential clinical application to assist the ophthalmologists for fast and accuracy retinal disease screening.

Non-arteritic anterior ischemic and glaucomatous optic neuropathy: Implications for neuroretinal rim remodeling with disease severity

PURPOSE

Post-acute non-arteritic ischemic optic neuropathy (NAION) and glaucomatous optic neuropathy (GON) can be difficult to differentiate clinically. Our objective was to identify optical coherence tomography (OCT) parameters to help differentiate these optic neuropathies.

METHODS

We compared 12 eyes of 8 patients with NAION and 12 eyes of 12 patients with GON, matched for age and visual field mean deviation (MD). All patients underwent clinical assessment, automated perimetry (Humphrey Field Analyzer II; Carl Zeiss Meditec, Dublin, CA, USA), and OCT imaging (Spectralis OCT2; Heidelberg Engineering, Heidelberg, Germany) of the optic nerve head and macula. We derived the neuroretinal minimum rim width (MRW), peripapillary retinal nerve fibre layer (RNFL) thickness, central anterior lamina cribrosa depth, and macular retinal thickness.

RESULTS

MRW was markedly thicker, both globally and in all sectors, in the NAION group compared to the GON group. There was no significant group difference in RFNL thickness, globally or in any sector, with the exception of the temporal sector that was thinner in the NAION group. The group difference in MRW increased with increasing visual field loss. Other differences observed included lamina cribrosa depth significantly greater in the GON group and significantly thinner central macular retinal layers in the NAION group. The ganglion cell layer was not significantly different between the groups.

CONCLUSIONS

The neuroretinal rim is altered in a dissimilar manner in NAION and GON and MRW is a clinically useful index for differentiating these two neuropathies. The fact that the difference in MRW between the two groups increased with disease severity suggests distinct remodelling patterns in response to differing insults with NAION and GON.

Correlations between Visual Performance and Chorioretinal Variables after Vitrectomy for the Idiopathic Macular Hole

Purpose

To investigate the relationships between visual function and the retinal and choroid microstructure in idiopathic macular hole patients after surgery.

Methods

A prospective study investigated changes in the fundus structure and visual function in 16 macular hole patients before and after surgery. Patients' best-corrected visual acuity (BCVA) and retinal sensitivity were measured by an EDTRS visual chart and microperimetry (MP1), respectively. The thickness of the retina and the blood supply to the retina and superficial choroid were detected by OCTA, and the choroidal capillary blood flow density was analysed with MATLAB. The thickness of the choroid and the aperture size of the macular hole were detected by Heidelberg OCT.

Results

Compared with before surgery and one month after surgery, the BCVA (3 months: 0.47 ± 0.27, before: 1.02 ± 0.22, 1 month: 0.66 ± 0.27, and P < 0.05) and the central sensitivity of the retina (3 months: 14.88 ± 2.87 dB, before: 8.76 ± 3.27 dB, 1 month: 12.22 ± 3.30 dB, and P < 0.05) were significantly improved three months after surgery. The change in BCVA was significantly correlated with the basal diameter (r = 0.677 and P = 0.004), the minimum diameter (r = 0.585 and P = 0.017), the macular hole cystoid height area index (r = -0.618 and P = 0.011), the central macular hole index (r = -0.727 and P = 0.001), the peripheral macular hole index (r = -0.758 and P = 0.001), the central tractional hole index (r = -0.717 and P = 0.002), the peripheral tractional hole index (r = -0.725 and P = 0.001), and changes in the peripheral blood vessel density of the choroid capillary layer (r = 0.585 and P = 0.0017). The change in central retinal sensitivity was correlated with the change in the superficial foveal avascular zone (FAZ; r = 0.520 and P = 0.039), change in the retinal superficial peripheral blood flow density (r = -0.503 and P = 0.047), change in the deep FAZ (r = 0.599 and P = 0.014), and change in the retinal deep peripheral blood flow density (r = -0.601 and P = 0.014).

Conclusions

The morphology of the macular hole as well as changes to the retinal and choroidal microstructure contributes to the recovery of visual function after surgery.

Evaluation of Macular Thickness Changes after Uncomplicated Phacoemulsification Surgery in Healthy Subjects and Diabetic Patients without Retinopathy by Spectral Domain OCT

PURPOSE

To assess differences in the evolution of macular thickness after uncomplicated phacoemulsification surgery between non-diabetic subjects and patients with diabetes mellitus (DM) without diabetic retinopathy (DR), using Spectral Domain OCT (SD-OCT).

METHODS

We performed a unicentric prospective study including one hundred and thirty-one eyes of 70 patients divided into two groups-34 well-controlled DM patients without DR and 36 non-diabetic subjects-who underwent phacoemulsification for cataract surgery. Eyes that developed pseudophakic cystoid macular edema (PCME) were excluded from the study, leaving us with 64 patients. Macular thickness was analyzed using Cirrus HD-OCT (Macular Cube 512 × 128 protocol) preoperatively and on postoperative days 7, 30, 90, and 180. For cases with information available for both eyes, one eye was randomly selected for analysis.

RESULTS

A total of 64 eyes from 64 patients were analyzed in this study. The mean value of HbA1c in the diabetic group was 7%. After uncomplicated cataract surgery, patients showed no increase of the foveal, parafoveal, and perifoveal retinal thickness on postoperative day 7. However, thickness values increased on days 30, 90, and 180 after surgery in both groups, and peak at 90 days. There was no difference in macular thickness before or after surgery between DM and non-diabetic patients (p = 0.540).

CONCLUSION

Macular thickness increases up to 6 months after uncomplicated cataract surgery in both DM patients without DR and non-diabetic subjects, with no differences between increases in both groups.

Retinal Examinations Provides Early Warning of Alzheimer's Disease

Patients with Alzheimer's disease have difficulty maintaining independent living abilities as the disease progresses, causing an increased burden of care on family caregivers and the healthcare system and related financial strain. This patient group is expected to continue to expand as life expectancy climbs. Current diagnostics for Alzheimer's disease are complex, unaffordable, and invasive without regard to diagnosis quality at early stages, which urgently calls for more technical improvements for diagnosis specificity. Optical coherence tomography or tomographic angiography has been shown to identify retinal thickness loss and lower vascular density present earlier than symptom onset in these patients. The retina is an extension of the central nervous system and shares anatomic and functional similarities with the brain. Ophthalmological examinations can be an efficient tool to offer a window into cerebral pathology with the merit of easy operation. In this review, we summarized the latest observations on retinal pathology in Alzheimer's disease and discussed the feasibility of retinal imaging in diagnostic prediction, as well as limitations in current retinal examinations for Alzheimer's disease diagnosis.

Posterior Segment Optical Coherence Tomography in Uncooperative Paediatric Patients Using Exo-Illumination and Microscope-Integrated Optical Coherence Tomography

BACKGROUND AND OBJECTIVE

To describe a non-invasive technique for the acquisition of retinal optical coherence tomography (OCT) scans in paediatric patients undergoing examination under general anaesthesia (EUA) using microscope-integrated OCT (MIOCT).

STUDY DESIGN

Prospective observational study Methods and Material: The study included 10 paediatric patients undergoing EUA for posterior segment pathology. These patients underwent OCT using MIOCT. No sclerotomy was made during imaging. The fundus was externally illuminated with a 25 gauge endoilluminator probe placed at the limbus and directed towards the posterior pole to aid in image acquisition by MIOCT (exo-illumination). Imaging for all patients was done by two trained vitreoretinal surgeons independently. Acquisition time was recorded for each surgeon. Interobserver variability in acquisition time and image quality was assessed to estimate the reliability of the novel imaging technique.

RESULTS

In nine cases (90%), MIOCT successfully imaged the posterior segment pathology while in one case (10%) of X-linked retinoschisis, it failed to detect an inner retinal break located anteriorly at the equator. The mean acquisition time for surgeons one and two was 211.75 ± 26.00 and 212.58 ± 23.47 seconds, respectively. There was no significant difference in total image acquisition time between the two surgeons (P = 1.0) and the findings of both surgeons were comparable for structural morphology. 4x4 mm-sized scans provided the best delineation in macular pathology, while a 16x16 mm scan size was best suited for localising the area of interest and post-equatorial pathology.

CONCLUSION

Using this technique acquisition of posterior segment OCT scans can be achieved non-invasively, using exo-illumination and MIOCT in paediatric patients undergoing EUA.

Prognostic Features of Preoperative OCT in Retinal Detachments: A Systematic Review and Meta-analysis

TOPIC

To evaluate the prognostic association between preoperative features seen on OCT imaging and postoperative visual acuity (VA) outcomes in rhegmatogenous retinal detachments (RRDs).

CLINICAL RELEVANCE

Currently, there is limited literature on the prognostic value of preoperative RRD OCT features.

METHODS

A literature search was conducted on Ovid MEDLINE, Ovid Embase, and Cochrane CENTRAL from inception to September 15, 2022. A meta-analysis was performed using a random-effects model. Quality of studies and evidence were assessed using the Joanna Briggs Institute tools and the Grading of Recommendations, Assessment, Development and Evaluation framework, respectively.

RESULTS

A total of 1671 eyes of 1670 patients from 29 observational studies were included. Of these, 89% of eyes had a macula-off RRD at presentation. The mean average duration of detachment was 15 ± 10 days. Most eyes (62%) underwent pars plana vitrectomy. Six preoperative OCT features were analyzed: height of retinal detachment (HRD) at the fovea, central macular thickness (CMT), disruption of the ellipsoid zone (EZ) and/or external limiting membrane (ELM), intraretinal cystic cavities (ICCs), outer retinal corrugations (ORCs), and macular detachment. A greater HRD was weakly associated with postoperative VA (Pearson correlation r = 0.35; 95% confidence interval [CI], 0.20-0.48; P < 0.01), and there was no change in this association throughout the postoperative follow-up period. The CMT was not associated with postoperative VA. Eyes with disruption of the EZ and/or ELM had a postoperative VA worse by 0.35 logarithm of the minimum angle of resolution (logMAR) (95% CI, 0.15-0.54; P < 0.01) or 3 Snellen lines. Eyes with ICCs had a postoperative VA worse by 0.14 logMAR (95% CI, 0.01-0.26; P < 0.01) or 2 Snellen lines. Eyes with ORCs did not have a significantly different postoperative VA than eyes without ORCs. Eyes with macular detachment had a postoperative VA worse by 0.15 logMAR (95% CI, -0.31 to 0.00; P = 0.02) or 2 Snellen lines. Overall, the quality of studies ranged from moderate to good (73%-100%). All associations had a low quality of evidence, with CMT being of very low quality.

CONCLUSION

Despite the low quality of evidence, a greater HRD, disruption of the EZ and/or ELM, presence of ICCs, and macular detachment were associated with a poor postoperative VA. We propose a standardized nomenclature for consistency and accuracy in reporting preoperative RRD OCT features for future studies.

A systematic survey of advances in retinal imaging modalities for Alzheimer's disease diagnosis

Recent advances in retinal imaging pathophysiology have shown a new function for biomarkers in Alzheimer's disease diagnosis and prognosis. The significant improvements in Optical coherence tomography (OCT) retinal imaging have led to significant clinical translation, particularly in Alzheimer's disease detection. This systematic review will provide a comprehensive overview of retinal imaging in clinical applications, with a special focus on biomarker analysis for use in Alzheimer's disease detection. Articles on OCT retinal imaging in Alzheimer's disease diagnosis were identified in PubMed, Google Scholar, IEEE Xplore, and Research Gate databases until March 2021. Those studies using simultaneous retinal imaging acquisition were chosen, while those using sequential techniques were rejected. "Alzheimer's disease" and "Dementia" were searched alone and in combination with "OCT" and "retinal imaging". Approximately 1000 publications were searched, and after deleting duplicate articles, 145 relevant studies focused on the diagnosis of Alzheimer's disease utilizing retinal imaging were chosen for study. OCT has recently been demonstrated to be a valuable technique in clinical practice as according to this survey, 57% of the researchers employed optical coherence tomography, 19% used ocular fundus imaging, 13% used scanning laser ophthalmoscopy, and 11% have used multimodal imaging to diagnose Alzheimer disease. Retinal imaging has become an important diagnostic technique for Alzheimer's disease. Given the scarcity of available literature, it is clear that future prospective trials involving larger and more homogeneous groups are necessary, and the work can be expanded by evaluating its significance utilizing a machine-learning platform rather than simply using statistical methodologies.

Long-acting formulation strategies for protein and peptide delivery in the treatment of PSED

The invigoration of protein and peptides in serious eye disease includes age-related macular degeneration, choroidal neovascularization, retinal neovascularization, and diabetic retinopathy. The transportation of macromolecules like aptamers, recombinant proteins, and monoclonal antibodies to the posterior segment of the eye is challenging due to their high molecular weight, rapid degradation, and low solubility. Moreover, it requires frequent administration for prolonged therapy. The long-acting novel formulation strategies are helpful to overcome these issues and provide superior therapy. It avoids frequent administration, improves stability, high retention time, and avoids burst release. This review briefly enlightens posterior segments of eye diseases with their diagnosis techniques and treatments. This article mainly focuses on recent advanced approaches like intravitreal implants and injectables, electrospun injectables, 3D printed drug-loaded implants, nanostructure thin-film polymer devices encapsulated cell technology-based intravitreal implants, injectable and depots, microneedles, PDS with ranibizumab, polymer nanoparticles, inorganic nanoparticles, hydrogels and microparticles for delivering macromolecules in the eye for intended therapy. Furthermore, novel techniques like aptamer, small Interference RNA, and stem cell therapy were also discussed. It is predicted that these systems will make revolutionary changes in treating posterior segment eye diseases in future.

Outcomes from the Retrospective Multicenter Cross-Sectional Study on Lamellar Macular Hole Surgery

Purpose

To analyze the functional and anatomical parameters of lamellar macular hole (LMH) surgery with internal limiting membrane peeling and determine which surgical technique provides the best visual outcome.

Methods

This is a retrospective multicenter cross-sectional study on patients who underwent pars plana vitrectomy (PPV) for LMH with or without combined phaco-vitrectomy, as well as gas-, air- or BSS-tamponade. Pre- and postoperative examination included best corrected visual acuity (BCVA) measurements for functional comparison and optical coherence tomography (OCT) scans to determine the contributing anatomical parameters.

Results

A total of 66 consecutive patients were included (age: 71.79 ± 8.52 years), of which 47 (71.2%) were diagnosed as tractional type LMH, and 19 patients (28.8%) as degenerative type. An epiretinal membrane (ERM) was present in 63 of the patients (95.5%), LMH-associated epiretinal proliferation (LHEP) was present in 19 patients (28.8%), and 16 patients (24.2%) had concomitant ERM and LHEP. In the group of tractional LMH, the mean central foveal thickness (CFT) was 81.1% thicker (P < 0.05) than in the degenerative group. Thirty-one patients (47.0%) underwent a combined phaco-vitrectomy procedure, while the rest underwent 23G, 25G or 27G PPV. Seventeen of the 66 patients received gas-tamponade (25.7%)-either SF₆ or C₃F₈, 26 received air-tamponade (39.4%), while the remaining 23 patients received balanced salt solution (BSS)-tamponade (34.9%) during vitrectomy. The total BCVA showed significant improvement postoperatively (p < 0.001) and accordingly in the following groups: tractional LMH type (p < 0.001), degenerative type (p < 0.001), simple PPV (p < 0.001), phaco-vitrectomy (p < 0.001), BSS injection (p < 0.01), gas-tamponade (p < 0.05). None of the patients included in the study developed a full thickness macular hole postoperatively.

Conclusion

PPV provided a high success rate and functional improvement for treating LMH for both tractional and degenerative types, as well as combined phaco-vitrectomy treatment when cataract was present.

Memorizing Structure-Texture Correspondence for Image Anomaly Detection

This work focuses on image anomaly detection by leveraging only normal images in the training phase. Most previous methods tackle anomaly detection by reconstructing the input images with an autoencoder (AE)-based model, and an underlying assumption is that the reconstruction errors for the normal images are small, and those for the abnormal images are large. However, these AE-based methods, sometimes, even reconstruct the anomalies well; consequently, they are less sensitive to anomalies. To conquer this issue, we propose to reconstruct the image by leveraging the structure-texture correspondence. Specifically, we observe that, usually, for normal images, the texture can be inferred from its corresponding structure (e.g., the blood vessels in the fundus image and the structured anatomy in optical coherence tomography image), while it is hard to infer the texture from a destroyed structure for the abnormal images. Therefore, a structure-texture correspondence memory (STCM) module is proposed to reconstruct image texture from its structure, where a memory mechanism is used to characterize the mapping from the normal structure to its corresponding normal texture. As the correspondence between destroyed structure and texture cannot be characterized by the memory, the abnormal images would have a larger reconstruction error, facilitating anomaly detection. In this work, we utilize two kinds of complementary structures (i.e., the semantic structure with human-labeled category information and the low-level structure with abundant details), which are extracted by two structure extractors. The reconstructions from the two kinds of structures are fused together by a learned attention weight to get the final reconstructed image. We further feed the reconstructed image into the two aforementioned structure extractors to extract structures. On the one hand, constraining the consistency between the structures extracted from the original input and that from the reconstructed image would regularize the network training; on the other hand, the error between the structures extracted from the original input and that from the reconstructed image can also be used as a supplement measurement to identify the anomaly. Extensive experiments validate the effectiveness of our method for image anomaly detection on both industrial inspection images and medical images.

Digital refocusing based on deep learning in optical coherence tomography

We present a deep learning-based digital refocusing approach to extend depth of focus for optical coherence tomography (OCT) in this paper. We built pixel-level registered pairs of en face low-resolution (LR) and high-resolution (HR) OCT images based on experimental data and introduced the receptive field block into the generative adversarial networks to learn the complex mapping relationship between LR-HR image pairs. It was demonstrated by results of phantom and biological samples that the lateral resolutions of OCT images were improved in a large imaging depth clearly. We firmly believe deep learning methods have broad prospects in optimizing OCT imaging.

MACULAR HOLE CLOSURE WITH TOPICAL STEROIDS

BACKGROUND AND OBJECTIVE

To report the outcomes of topical difluprednate 0.05% use in the closure of full-thickness macular holes.

PATIENTS AND METHODS

Retrospective chart review of 4 patients with full-thickness macular holes who received difluprednate drops 4 times daily for a minimum of 12 weeks. Main outcome measures were macular hole status assessed with optical coherence tomography, visual acuity, intraocular pressure, and complications of treatment.

RESULTS

All patients had macular hole closure within 12 weeks of difluprednate exposure. Mean time to macular hole closure was 5 weeks (range, 2-12 weeks). Visual acuity improved with macular hole closure. Average baseline visual acuity was 20/42. Average visual acuity after macular hole closure was 20/26 (P = 0.14). Two patients experienced increased intraocular pressure with topical steroid use.

CONCLUSION

Exposure to difluprednate in this cohort of patients with full-thickness macular holes was associated with reduced macular edema, macular hole closure, and visual improvement.

Clinical explainable differential diagnosis of polypoidal choroidal vasculopathy and age-related macular degeneration using deep learning

BACKGROUND

This study aims to achieve an automatic differential diagnosis between two types of retinal pathologies with similar pathological features - Polypoidal choroidal vasculopathy (PCV) and wet age-related macular degeneration (AMD) from volumetric optical coherence tomography (OCT) images, and identify clinically-relevant pathological features, using an explainable deep-learning-based framework.

METHODS

This is a retrospective study with data from a cross-sectional cohort. The OCT volume of 73 eyes from 59 patients was included in this study. Disease differentiation was achieved through single-B-scan-based classification followed by a volumetric probability prediction aggregation step. We compared different labeling strategies with and without identifying pathological B-scans within each OCT volume. Clinical interpretability was achieved through normalized aggregation of B-scan-based saliency maps followed by maximum-intensity-projection onto the en face plane. We derived the PCV score from the proposed differential diagnosis framework with different labeling strategies. The en face projection of saliency map was validated with the pathologies identified in Indocyanine green angiography (ICGA).

RESULTS

Model trained with both labeling strategies achieved similar level differentiation power (>90%), with good correspondence between pathological features detected from the projected en face saliency map and ICGA.

CONCLUSIONS

This study demonstrated the potential clinical application of non-invasive differential diagnosis using AI-driven OCT-based analysis, with minimal requirement of labeling efforts, along with clinical explainability achieved through automatically detected disease-related pathologies.

OCT guided micro-focal ERG system with multiple stimulation wavelengths for characterization of ocular health

Inherited retinal disorders and dry age-related macular degeneration are characterized by the degeneration and death of different types of photoreceptors at different rate and locations. Advancement of new therapeutic interventions such as optogenetics gene therapy and cell replacement therapies are dependent on electrophysiological measurements at cellular resolution. Here, we report the development of an optical coherence tomography (OCT) guided micro-focal multi-color laser stimulation and electroretinogram (ERG) platform for highly localized monitoring of retina function. Functional evaluation of wild type and transgenic pigs affected by retinal degeneration was carried out using OCT guided micro-focal ERG (μfERG) with selected stimulation wavelengths for S, M and L cones as well as rod photoreceptors. In wild type pigs, μfERG allowed functional recording from rods and each type of cone photoreceptor cells separately. Furthermore, functional deficits in P23H transgenic pigs consistent with their retinal degeneration phenotype were observed, including decrease in the S and M cone function and lack of rod photoreceptor function. OCT guided μfERG based monitoring of physiological function will enable characterization of animal models of retinal degenerative diseases and evaluation of therapeutic interventions at the cellular level.